This is still in progress / experimental, currently it is only
implemented for normal gemma MQA attention layers, and no
parallelism is added yet for backward pass.
Since we need to remember all activations from all layers, the
forward pass was also reimplemented with a new activation data
structure.
Remove extra Dot() overload
MatVecAdd always adds, use MatVecT<kAdd> if conditional.
Remove ununsed MatVecAddLoop and MatVecLoop
No longer tsan-verify even_odd
PiperOrigin-RevId: 631377279
Move Path into io.h and use for opening files.
Removes dependency of gemma_lib on args.
Separate Windows codepath instead of emulating POSIX functions.
Plus lint fixes.
PiperOrigin-RevId: 626279004
- Allow scaling of SFP weights
- Allow using uncompressed weights
- Do not try to compress weights in the main model calls
- Reduce code duplication in weight handling with some macros
Co-authored-by: Eugene Kliuchnikov <eustas@google.com>
Co-authored-by: Thomas Fischbacher <tfish@google.com>
Co-authored-by: Zoltan Szabadka <szabadka@google.com>
Jan Wassenberg
Zoltan Szabadka
Paul Chang
Sam Kaufman
Luca Versari
enum-class
Austin Huang